Improving Remote Sensing-based Flood Mapping using GIS (terrain-based) Analysis

This presentation was given as part of the GIS Day@KU symposium on November 15, 2017. For more information about GIS Day@KU activities, please see http://gis.ku.edu/gisday/2017/PLATINUM SPONSORS: KU Department of Geography and Atmospheric Science KU Institute for Policy & Social Research GOLD SPONSORS: KU Libraries State of Kansas Data Access & Support Center (DASC) SILVER SPONSORS: Bartlett & West Kansas Applied Remote Sensing Program KU Center for Global and International Studies BRONZE SPONSORS: Boundles

NASAs Mid-Atlantic Communities and Areas at Intensive Risk Demonstration: Translating Compounding Hazards to Societal Risk

Remote sensing provides a unique perspective on our dynamic planet, tracking changes and revealing the course of complex interactions. Long term monitoring and targeted observation combine with modeling and mapping to provide increased awareness of hydro-meteorological and geological hazards. Disasters often follow hazards and the goal of NASAs Disasters Program is to look at the earth as a highly coupled system to reduce risk and enable resilience. Remote sensing and geospatial science are used as tools to help answer critical questions that inform decisions. Data is not the same as information, nor does understanding of processes necessarily translate into decision support for disaster preparedness, response and recovery. Accordingly, NASA is engaging the scientific and decision-support communities to apply remote sensing, modeling, and related applications in Communities and Areas at Intensive Risk (CAIR). In 2017, NASAs Applied Sciences Disasters Program hosted a regional workshop to explore these issues with particular focus on coastal Virginia and North Carolina. The workshop brought together partners in academia, emergency management, and scientists from NASA and partnering federal agencies to explore capabilities among the team that could improve understanding of the physical processes related to these hazards, their potential impact to changing communities, and to identify methodologies for supporting emergency response and risk mitigation. The resulting initiative, the mid-Atlantic CAIR project, demonstrates the ability to integrate satellite derived earth observations and physical models into actionable, trusted knowledge. Severe storms and associated storm surge, sea level rise, and land subsidence coupled with increasing populations and densely populated, aging critical infrastructure often leave coastal regions and their communities extremely vulnerable. The integration of observations and models allow for a comprehensive understanding of the compounding risk experienced in coastal regions and enables individuals in all positions make risk-informed decisions. This initiative uses a representative storm surge case as a baseline to produce flood inundation maps. These maps predict building level impacts at current day and for sea level rise (SLR) and subsidence scenarios of the future in order to inform critical decisions at both the tactical and strategic levels. To accomplish this analysis, the mid-Atlantic CAIR project brings together Federal research activities with academia to examine coastal hazards in multiple ways: 1) reanalysis of impacts from 2011 Hurricane Irene, using numerical weather modeling in combination with coastal surge and hydrodynamic, urban inundation modeling to evaluate combined impact scenarios considering SLR and subsidence, 2) remote sensing of flood extent from available optical imagery, 3) adding value to remotely sensed flood maps through depth predictions, and 4) examining coastal subsidence as measured through time-series analysis of synthetic aperture radar observations. Efforts and results are published via ArcGIS story maps to communicate neighborhoods and infrastructure most vulnerable to changing conditions. Story map features enable time-aware flood mapping using hydrodynamic models, photographic comparison of flooding following Hurricane Irene, as well as visualization of heightened risk in the future due to SLR and land subsidence

Floodwater Depth Estimation Tool - Coastal Version (FwDET-C)

No abstract availabl

The Global Flood Partnership Conference 2017 - From hazards to impacts

From 27 – 29 June 2017, the 2017 Global Flood Partnership Conference was held at the University of Alabama, U.S.A. More than 90 participants attended the conference coming from 11 different countries in 5 continents. They represented 56 institutions including international organisations, the private sector, national authorities, universities, governmental research agencies and non-profit organisations. Each year, floods cause devastating losses and damage across the world. Growing populations in ill-planned flood-prone coastal and riverine areas are increasingly exposed to more extreme rainfall events. With more population and economic assets at risk, governments, banks, international development and relief agencies, and private firms are investing in flood reduction measures. However, in many countries, the flood risk is not managed optimally because of a lack of scientific data and methods or a communication gap between science and risk managers. The Global Flood Partnership was launched in 2014 and is a cooperation framework between scientific organisations and flood disaster managers worldwide to develop flood observational and modeling infrastructure, leveraging on existing initiatives for better predicting and managing flood disaster impacts and flood risk globally. The conference theme was “From hazards to impacts” and participants had the opportunity to showcase their latest relevant research and activities. As usual, the advances and success stories of the Partnership were reviewed and the next steps to further strengthen the GFP were discussed. As in past meetings, participants had numerous opportunities to present their work, exchange ideas, and turn it into a lively and successful meeting. This included a "Marketplace of Ideas" session, "Ignite" talks, Problem-solving session, workshops, poster pitch session and breakout groups.JRC.E.1-Disaster Risk Managemen

A global network for operational flood risk reduction

Every year riverine flooding affects millions of people in developing countries, due to the large population exposure in the floodplains and the lack of adequate flood protection measures. Preparedness and monitoring are effective ways to reduce flood risk. State-of-the-art technologies relying on satellite remote sensing as well as numerical hydrological and weather predictions can detect and monitor severe flood events at a global scale. This paper describes the emerging role of the Global Flood Partnership (GFP), a global network of scientists, users, private and public organizations active in global flood risk management. Currently, a number of GFP member institutes regularly share results from their experimental products, developed to predict and monitor where and when flooding is taking place in near real-time. GFP flood products have already been used on several occasions by national environmental agencies and humanitarian organizations to support emergency operations and to reduce the overall socio-economic impacts of disasters. This paper describes a range of global flood products developed by GFP partners, and how these provide complementary information to support and improve current global flood risk management for large scale catastrophes. We also discuss existing challenges and ways forward to turn current experimental products into an integrated flood risk management platform to improve rapid access to flood information and increase resilience to flood events at global scale

Spatial description of soil properties through landscape-pedogenesis modelling

Research Doctorate - Doctor of Philosophy (PhD)Soil is one of the most important substances or zones in the natural system both as a substratum for life and as a component in a variety of processes. Soil characteristics play a major role in most geomorphological and hydrological processes. Describing soil spatial and temporal dynamics has been therefore important but is yet to be adequately achieved. In recent years there is a growing recognition that a mechanistic landscape-pedogenesis approach is needed in order to fully capture soil dynamics. However this approach has not been fully implemented due to the immense complexities in integrating soil and landscape processes and the many uncertainties within this merger. In this work an interdisciplinary approach is adopted in which geomorphological processes at a landscape scale are mechanistically linked to pedological processes at a profile scale. The complexities of this merger are reduced by a novel mathematical approach which couples physically-based equations and transition matrices. The resulting model (mARM3D) explicitly describes the soil profile for every point on the landscape while remaining computationally efficient. This allows simulation of large-scale and long-term soil evolution as a function of a various processes. In this thesis the model physics was kept simple, simulating only surface armouring (selective erosion) and mechanical weathering. This simplicity is important for the model development as it allows easier interpretation of cause and effect in the results. The modelling approach and physics are described in detail in this thesis. The model is evaluated and found to provide a good match to a traditional physically-based model and to laboratory weathering results. The model is used to study three major pedological concepts. The first concept is the depth dependency of bedrock and soil weathering. The effect of weathering rate changes within the soil-profile is examined by simulating long-term soil evolution with two well known soil production functions, the exponential decline and the “humped”. The results show that the differences between the two weathering functions affected not only the soil vertical and spatial distribution but also the local erosion regime. The second concept examined is the relationship between soil and topography. This was initially studied with a new methodology of spatially-explicit calculation of the area-slope equation and hypsometric integral. With this methodology the soil-topography relationship is identified but cannot be quantitatively described. Using the model the area-slope-soil relationship is quantitatively calculated for the first time. The results show that the area-slope-soil relationship has a similar scaling under different conditions. This prompts a possible analytical solution for this relationship which may have important implications for soil mapping and various modelling frameworks (e.g. landform evolution). The third concept examined is the effect of climatic changes on long-term soil evolution. Soil evolution is simulated with mARM3D using a Late Quaternary (400,000 year) climate oscillation input. The results show, for the first time, that the affect of climatic forcing on soil evolution has very distinct spatial and temporal trends. The magnitude in which the climatic forcing affects soil evolution varies considerably in space to the extent where different parts of the hillslope have opposite evolutionary trends. The results also show that the timescale of soil adjustment to climatic changes is substantial and spatially variable. These results have great implications for pedogenesis and long-term soil-related modelling. The study, presented here, is an initial stage in the development of this modelling framework. The last chapter provides a strategic plan for the future development and usage of the mARM3D model

Soil-landscape response to mid and late Quaternary climate fluctuations based on numerical simulations

We use a numerical dynamic soil-landscape model to study one aspect of the spatio-temporal soil-landscape evolution process, the effect of climatic fluctuations on soil grading distribution in space and time in response to the interplay between physical weathering and surface erosion (soil mineralogical fluxes). We simulate a synthetic soil-landscape system over the middle and late Quaternary (last 400 ka). The results show that (1) soil-landscape response to climate change is non-linear and highly spatially variable, even at hillslope scale; and (2) soil-landscape adjustment to climate change can lag tens of thousands of years and is both spatially and temporally variable. We propose that the legacy of past climatic condition (i.e. last glacial maximum) in modern soil-landscape systems vary considerably in space. This implies that the spatiotemporal uniformity in which soil is typically described in Earth system modeling and analysis (e.g. carbon cycle) grossly underestimates their actual complexity

Tropical cyclones as a driver of global sediment flux

The world's rivers deliver 19 billion tonnes of sediment to the coastal zone annually. The sediment supplied to the coastal zone is of significant importance for a variety of reasons, for example in acting as a vector for nutrients as well as in supplying sediment to coastal landforms such as deltas and beaches that can buffer those landforms from erosion and flooding. A greater understanding of the factors governing sediment flux to the oceans is therefore a key research gap. The non-linear relationship between river discharge and sediment flux implies that the global sediment flux may be disproportionately driven by large floods. Indeed, in our recent empirical research we have demonstrated that changes in the track locations, frequency and intensity of tropical storms in recent decades exert a significant control on the sediment flux emanating from the Mekong River. Since other large rivers potentially affected by tropical storms are known to make a significant contribution to the global sediment flux, this raises the question of the extent to which such storms play a significant role in controlling sediment loads at the global scale. In this paper we address that question by employing a global hydrological model (WBMsed) in order to predict runoff and sediment load forced by recent historical climate scenarios `with' and `without' tropical cyclones. We compare the two scenarios to (i) make the first estimate of the global contribution of sediment load forced by tropical storms; (ii) evaluate how that contribution has varied in recent decades and to (iii) explore variations in tropical-storm driven sediment loads in selected major river basins that are significantly affected by such storms